Is there a common Java utility to break a list into batches?

java

list-partitioning

google-guava

stream-api

byNikita Barsukov·Oct 18, 2024

The Stream API in Java 8+ lets you divide a List into smaller chunks using the subList() method:

// Who says Java can't be a one-liner-friendly language?
List<List<T>> batches = IntStream.range(0, list.size())
    .filter(i -> i % batchSize == 0) 
    .mapToObj(i -> list.subList(i, Math.min(i + batchSize, list.size()))) // Min? Max? Confused? Nah, just Java things...
    .collect(Collectors.toList());

Substitute T with your list's item type and batchSize with the intended batch size. This streamlined approach neatly segregates your list into manageable groups.

Exploring libraries for list partitioning

When it comes to splitting lists, two libraries quickly come to mind:

Google Guava's Lists.partition(): Works well in situations where you don't mind the final sublist having fewer items.
Apache Commons Collections' ListUtils.partition(): For those who prefer staying within the Apache realm.

Writing custom solutions might seem appealing but leveraging well-tested libraries like these ensures reliability in various scenarios.

Practicality of Stream API in batch processing

The Stream API led to a sea change in Java programming. Here's why it's a worthy tool for list partitioning:

Code legibility: Build up complex tasks with chained operations for a more understandable codebase.
Functional approach: Use lambdas and method references for a clearer, expressive way of programming.
Parallel capability: Simple tweaks can boost performance on multi-core processors by running stream operations concurrently.

Diving into Google Guava

As an indispensable toolset for Java developers, Google Guava offers more than simple list partitioning:

Immutable collections: For read-only, thread-safe data structures.
Cache utilities: Handy utilities for implementing in-memory caching with flexible eviction strategies.
A ton more: With features like collection helpers, string processing, and I/O utilities, your toolbox might need an upgrade.

Handling edge cases in batching

Partitioning a list has its nuances. Understanding them can help avoid future pitfalls:

Order continuity: In some contexts, retaining the initial sequence in the batches is vital.
Remainder handling: Deciding to extend the last batch with remaining items or to discard it if it's incomplete depends on your application requirements.
Source list safety: Always work with immutable copies to avoid inadvertent changes to the original list.